import random
"""
Generate N random 1s in a zero-based matrix.
Strategy:
- Treat the matrix as a flat index space [0 .. rows*cols - 1].
- Randomly pick unique positions using a helper set.
- Convert each chosen flat index back to (row, col).
- This avoids repeatedly searching for empty cells and keeps the logic simple.
"""
# Print the matrix
def print_matrix(matrix):
for row in matrix:
print(" ".join(str(v) for v in row))
# Allocate a rows×cols matrix initialized to zero
def allocate_matrix(rows, cols):
# List comprehension keeps the code compact and expressive
return [[0 for _ in range(cols)] for _ in range(rows)]
# Generate N random 1s in a zero-based matrix
def generate_random_matrix(rows, cols, count):
total = rows * cols
if count > total:
raise ValueError("Requested more 1s than available cells.")
matrix = allocate_matrix(rows, cols)
# Use a set to ensure unique positions
chosen = set()
# Draw unique positions
while len(chosen) < count:
index = random.randrange(total)
chosen.add(index)
# Convert flat indices to (row, col)
for index in chosen:
r = index // cols
c = index % cols
matrix[r][c] = 1
return matrix
# Example usage
if __name__ == "__main__":
rows = 5
cols = 7
number_of_ones = 10
result = generate_random_matrix(rows, cols, number_of_ones)
print_matrix(result)
"""
run:
1 0 0 0 0 0 0
0 0 1 0 1 0 0
1 1 0 0 0 1 1
0 0 0 0 1 0 1
0 0 1 0 0 0 0
"""
